Spatially hierarchical factor models: building a vulnerability index to dengue fever in Uruguay

Spatially hierarchical factor models: building a vulnerability index to dengue fever in Uruguay

Alexandra M. Schmidt
IM-UFRJ, Brazil

We introduce a spatially hierarchical factor model, or a vulnerability
index, to measure dengue fever in Uruguay. Our proposal combines spatial
information among different municipalities across the region (large scale
information) with census tracts information at the municipality level (small
scale information). Aedes aegypti, the main dengue fever transmitting
vector, was reintroduced in Uruguay in 1997 with no cases of the disease
been registered up to this point in time. It is of great importance to point
the regions of the country which are vulnerable to the reintroduction of the
disease. It is common to observe, in social studies, social indices built
based on sets of indicators observed on census tract level of municipalities
across the countries. In our sample the number of census tracts vary
significantly, ranging from as low as 16 (Bella Union) up to 1012
(Montevideo) tracts. A simple comparison with a benchmark procedure, one
which aggregates observations at the municipal level before building the
index, suggests that our vulnerability index is more sensitive to local
characteristics and, therefore, more capable of capturing subtle differences
across regions of the country. Our factor model entertains point referenced
data at the country level and areal data within municipalities. We expect
that within a municipality, census tracts which are close together, tend to
have similar values of the variables, and behaving on a more independently
fashion if the tracts are far apart. On the other hand, in the country
level, one expects that index values vary smoothly across the
municipalities. More specifically, we combine the information available on p
variables measured at n_i, (i=1,…,n) census tracts across n
municipalities. The municipality size (number of tracts) is taken into
account and provide a tool of weighing the contribution of a variable
(according to its location) to the overall vulnerability index. Moreover,
different from standard procedures, independence across locations is not
imposed.